random-forests

There are 4 repositories under random-forests topic.

JuliaAI / DecisionTree.jl
Julia implementation of Decision Tree (CART) and Random Forest algorithms
julia machine-learning decision-tree random-forests classification regression
Language:Julia 352
PacktWorkshops / The-Python-Workshop
A New, Interactive Approach to Learning Python
python machine-learning types structure algorithms data-science pytorch gridsearchcv randomizedsearchcv linear-regression logistic-regression random-forests
Language:Jupyter Notebook 253
FarrellDay / miceRanger
miceRanger: Fast Imputation with Random Forests in R
r mice random-forests missing-data imputation-methods machine-learning missing-values
Language:R 64
jjfiv / fastrank
My most frequently used learning-to-rank algorithms ported to rust for efficiency. Try it: "pip install fastrank".
rust machine-learning learning-to-rank ranklib coordinate-ascent random-forests
Language:Rust 48
neurodata / ProgLearn
NeuroData's package for exploring and using progressive learning algorithms
classification continual-learning decision-trees deep-learning deep-neural-networks domain-adaptation random-forests transfer-learning
Language:Jupyter Notebook 35
forestry-labs / Rforestry
bagging boosting causal-inference interpretability machine-learning monotonic-constraints r r-package random-forest random-forests trees
Language:C++ 34
CBravoR / AdvancedAnalyticsLabs
Analytics labs notebooks for Statistics and Business School students
keras cnn credit-scoring text-mining revenue-management embeddings neural-networks bond-pricing basel-capital-requirements image-classification deep-learning random-forests xgboost
Language:Jupyter Notebook 30
disentangled-attribution-curves
csinva / disentangled-attribution-curves
Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"
interpretability random-forests machine-learning scikit-learn python statistics explainable-ai boosting ml ai stats random-forest ensemble-model feature-importance feature-engineering artificial-intelligence
Language:Python 25
bcgov / wetlandmapR
Scripts, tools and example data for mapping wetland ecosystems using data driven R statistical methods like Random Forests and open source GIS
package mapping-wetland-ecosystems wetland-model raster rsaga saga-gis data-driven random-forests statistical-methods random-forest british-columbia
Language:R 17
jjbrophy47 / dare_rf
Machine Unlearning for Random Forests
machine-unlearning random-forests data-removal
Language:Python 17
neurodata / df-dn-paper
Conceptual & empirical comparisons between decision forests & deep networks
classification decision-trees deep-learning deep-neural-networks machine-learning random-forests
Language:Jupyter Notebook 17
QSAR-activity-cliff-experiments
MarkusFerdinandDablander / QSAR-activity-cliff-experiments
Exploring QSAR Models for Activity-Cliff Prediction
deep-learning extended-connectivity-fingerprints graph-neural-networks machine-learning molecular-property-prediction molecular-representation qsar-models activity-cliff-prediction activity-cliffs binding-affinity-prediction physicochemical-descriptors graph-isomorphism-networks circular-fingerprints morgan-fingerprints k-nearest-neighbours multilayer-perceptrons random-forests supervised-machine-learning
Language:Jupyter Notebook 15
darth-c0d3r / deep-neural-decision-forests
A model combining Deep Neural Networks and (Stochastic) Random Forests.
deep-learning deep-neural-networks neural-networks random-forests decision-trees
Language:Python 14
tweichle / Predicting-Baseball-Statistics
Predicting Baseball Statistics: Classification and Regression Applications in Python Using scikit-learn and TensorFlow-Keras
machine-learning data-visualization supervised-learning predictive-modeling exploratory-data-analysis logistic-regression regularization cross-validation python data-science oversampling decision-trees random-forests support-vector-machines xgboost linear-regression ridge-regression lasso-regression elastic-net k-nearest-neighbors
Language:Jupyter Notebook 14
jseluis / artificial_intelligence_for_trading
Artificial Intelligence for Trading
machine-learning algorithm-trading artificial-intelligence natural-language-processing pytorch random-forests quants time-series portifolio-optimization risk-analysis sentiment-analysis numpy pandas zipline lstm
Language:HTML 12
UnixJunkie / orf
OCaml Random Forests
classification regression machine-learning statistical-modeling ocaml-library random-forests out-of-bag bagging bootstrap-aggregation
Language:OCaml 8
TrainingByPackt / The-Python-Workshop
Become a proficient, productive and powerful programmer with Python
python cython python37 machine-learning pytorch gridsearchcv logistic-regression random-forests histogram histograms numpy pandas
Language:Jupyter Notebook 7
jgeofil / mycorrhiza-algorithm
Combining phylogenetic networks and Random Forests for prediction of ancestry from multilocus genotype data
mycorrhiza splitstree ancestry population-genetics phylogenetics machine-learning structure admixture random-forests dimensionality-reduction multilocus-genotype-data analysis
Language:Python 6
BioGenies / CancerGram
Predicts anticancer peptides using random forests trained on the n-gram encoded peptides. The implemented algorithm can be accessed from both the command line and shiny-based GUI.
peptide-identification anticancer-peptides bioinformatics r-package random-forests n-gram k-mer
Language:R 4
eacheson / machine-learning-gazetteer-matching
Cross-gazetteer record linking of natural features in Switzerland using machine learning (random forests) and handcrafted rules.
notebooks machine-learning random-forests geonames switzerland python
Language:HTML 4
lyraxvincent / Data-Science-Machine-Learning-Portfolio
Portfolio Projects through my Data Science and Machine Learning Course program.
data-science machine-learning portfolio python knn-algorithm regression-algorithms decision-trees random-forests kmeans-algorithm pca svm
Language:Jupyter Notebook 4
Shahrukh2016 / Retail_Sales_Prediction
Revolutionize sales forecasting for Rossmann stores with our high-accuracy XGBoost model, leveraging data analysis, feature engineering, and machine learning to predict sales up to six weeks in advance.
data-analysis data-cleaning data-gathering data-preprocessing decision-trees exploratory-data-analysis feature-engineering lightgbm machine-learning model-evaluation model-selection one-hot-encoding outlier-detection random-forests regression-analysis regularization statistical-analysis transformation visualization xgboost
Language:Jupyter Notebook 4
jjfiv / poetry-identification
Poetry Identification Code from my dissertation runs on zip files containing DJVUXML from the Internet Archive.
djvuxml internet-archive poetry random-forests machine-learning digital-humanities
Language:Rust 3
mlpapers / ensemble-learning
Awesome papers on Ensemble Learning
ensemble-learning random-forests boosting gradient-boosting awesome awesome-list
3
rlleshi / MachineLearning
Some fundamental machine learning and data analysis techniques are revisited here through practical projects
machine-learning-models random-forests svn logistic-regression data-analysis data-science pca clustering xgboost talos deep-learning neural-network
Language:Jupyter Notebook 3
saimj7 / Machine-Learning-Algorithms
ML algorithms and applications from famous papers; simple theory; solid code.
logistic-regression face-recognition machine-learning support-vector-machines xor-problem image-classification decision-trees k-means-clustering random-forests
Language:Python 3
sorooshsorkhani / RankLib-Gini
Gini feature importance for RankLib random forests:
ranklib random-forests ranklib-gini gini gini-importance learning-to-rank
Language:Python 3
JalalAl-Tamimi / Intro-Random-Forests
This repo contains material for a workshop on Random Forests in phonetics/phonology research
random-forests conditional-inference-trees ranger glm phonology
Language:HTML 2
milesdwilliams15 / RFA
RFA package for implementing random forest adjustment.
random-forests r-package
Language:R 2
msarnacki / online-news-popularity-classification
This was a binary classification task in which I had to determine if and article got at least 1400 shares. I wanted to use few different machine learning algorithms to compare their accuracy on that data. I chose to use: Decision Tree, Random Forests and Multi Layer Perceptron.
machine-learning-algorithms classification multi-layer-perceptron random-forests decision-trees python pandas scikit-learn
Language:Jupyter Notebook 2
chloestipinovich / Grass-Pollen-Forecasting
This is the repository used to make the project titled 'Grass Pollen in Cape Town: A Comparison of Generalised Additive Models and Random Forests' by Sky Cope and Chloë Stipinovich.
random-forest generalised-additive-models shiny-apps pollen forecasting grass-pollen-forecasting saao cape-town random-forests weather
Language:R 1
DAndresSanchez / Placements_Multiple_Linear_Regression
Work placement salaries analysis through multiple linear regression and their occurrence based on qualifications and work experience.
multiple-linear-regression random-forests ridge-regression lasso-regression logistic-regression knn-classifier
Language:Jupyter Notebook 1
jesussantana / IBM-Machine-Learning-with-Python
This Machine Learning with Python course dives into the basics of machine learning using an approachable, and well-known, programming language
unsupervised-learning machine-learning random-forests dimensionality-reduction data-science regression-models clustering decision-trees python
Language:Jupyter Notebook 1
Lavanyask03 / income
Binary Classification of incomes as <50k or >50k using decision trees and random forests.
decision-trees random-forests r machine-learning
Language:Jupyter Notebook 1
priyanshkedia04 / Project-Predict-Employee-Turnover-with-scikit-learn
Decision trees and Random forests using scikit-learn and Python to build an employee churn prediction application with interactive controls
employee-turnover random-forests decision-trees python scikit-learn machine-learning
Language:Jupyter Notebook 1
TrentBrunson / Machine_Learning
Supervised Machine Learning using SciKit and other tools to do PCA, SVM, random forests, etc. for facial recognition and predictive decision making.
machine-learning pca svm random-forests scikitlearn-machine-learning predictive-analytics facial-recognition
Language:Python 1

random-forests

JuliaAI / DecisionTree.jl

PacktWorkshops / The-Python-Workshop

FarrellDay / miceRanger

jjfiv / fastrank

neurodata / ProgLearn

forestry-labs / Rforestry

CBravoR / AdvancedAnalyticsLabs

csinva / disentangled-attribution-curves

bcgov / wetlandmapR

jjbrophy47 / dare_rf

neurodata / df-dn-paper

MarkusFerdinandDablander / QSAR-activity-cliff-experiments

darth-c0d3r / deep-neural-decision-forests

tweichle / Predicting-Baseball-Statistics

jseluis / artificial_intelligence_for_trading

UnixJunkie / orf

TrainingByPackt / The-Python-Workshop

jgeofil / mycorrhiza-algorithm

BioGenies / CancerGram

eacheson / machine-learning-gazetteer-matching

lyraxvincent / Data-Science-Machine-Learning-Portfolio

Shahrukh2016 / Retail_Sales_Prediction

jjfiv / poetry-identification

mlpapers / ensemble-learning

rlleshi / MachineLearning

saimj7 / Machine-Learning-Algorithms

sorooshsorkhani / RankLib-Gini

JalalAl-Tamimi / Intro-Random-Forests

milesdwilliams15 / RFA

msarnacki / online-news-popularity-classification

chloestipinovich / Grass-Pollen-Forecasting

DAndresSanchez / Placements_Multiple_Linear_Regression

jesussantana / IBM-Machine-Learning-with-Python

Lavanyask03 / income

priyanshkedia04 / Project-Predict-Employee-Turnover-with-scikit-learn

TrentBrunson / Machine_Learning